A platform for quantum computing

Osama M. Raisuddin, Suvranu De

E. Wes Bethel, Mercy G. Amankwah, J. T. Balewski +4 more

The focus of this Visualization Viewpoints article is to provide some background on quantum computing (QC), to explore ideas related to how visualization helps in understanding QC, and examine how QC might be useful for visualization with the growth and maturation of both technologies in the future. In a quickly evolving technology landscape, QC is emerging as a promising pathway to overcome the growth limits in classical computing. In some cases, QC platforms offer the potential to vastly outperform the familiar classical computer by solving problems more quickly or that may be intractable on any known classical platform. As further performance gains for classical computing platforms are limited by diminishing Moore's Law scaling, QC platforms might be viewed as a potential successor to the current field of exascale-class platforms. While present-day QC hardware platforms are still limited in scale, the field of quantum computing is robust and rapidly advancing in terms of hardware capabilities, software environments for developing quantum algorithms, and educational programs for training the next generation of scientists and engineers. After a brief introduction to QC concepts, the focus of this article is to explore the interplay between the fields of visualization and QC. First, visualization has played a role in QC by providing the means to show representations of the quantum state of single-qubits in superposition states and multiple-qubits in entangled states. Second, there are a number of ways in which the field of visual data exploration and analysis may potentially benefit from this disruptive new technology though there are challenges going forward.

Hansika Weerasena, Prabhat Mishra

Balwinder Sodhi

As the practical Quantum Computing Platforms (QCPs) rapidly become a reality, it is desirable to harness their true potential in software applications. Thus it becomes important to determine the implications of QCPs for software architecture. In this paper we present the in-depth examination of state-of-the-art QCPs for identifying all such characteristics of a QCP that are relevant from software architecture perspective. Lack of a native quantum operating system, a hard dependency on quantum algorithms, the lower level of programming abstractions are few, out of many, examples of QCP characteristics which may affect architecture of quantum software applications. Key contributions of this paper include identifying: i) The general architecture of a QCP, ii) The programming model which is typically used when developing software for a QCP, iii) Architecturally significant characteristics of QCPs and iv) The impact of these characteristics on various Quality Attributes (QAs). We show that except performance and scalability, most of the other QAs (e.g. maintainability, testability, reliability etc.) are adversely affected by different characteristics of a QCP.

Siddh Agarwal, Gio Abou Jaoude, Avery M. Leider +1 more

Addala Satyanarayana Varma, Ch. E.S. Sindhu Priya, J. Sudhakar

Quantum Computing (QC) has evolved into a computational model that can potentially solve problems of classes that cannot be solved by classical systems. This review gives a discussion on the innovation of software frameworks, experimental platforms and quantum computing tools used to compute quantum algorithm development, simulation and implementation. It concentrates on widely used programming environments, which compile abstract quantum models into practical workflows, including Cirq, TensorFlow Quantum, ProjectQ and Qiskit. The paper, besides describing the long-lasting problems related to scalability, error correction, and hardware reliability, also considers the architecture of the modern quantum computing platforms. Finally, new advances are outlined, such as quantum cloud service and the integration of artificial intelligence and quantum computing, and their role in the development of QC to viable and lucrative deployments. All in all, the discussion suggests that even now quantum computing still needs to be taken to the next level in terms of hardware infrastructure and software development that would allow progressing to the next stage of quantum technology testing and implementation.